Explainable AI at NeurIPS 2019

The 33rd annual NeurIPS conference has now wrapped up. By the numbers, NeurIPS has become a behemoth, with over 1,400 papers accepted and around 13,000 people registered. The quickly growing field of Explainable AI (XAI) made a noticeable appearance in this multitude of papers and people. Additionally, many papers not geared specifically toward explainability turned … Continue reading “Explainable AI at NeurIPS 2019”

Explainable AI goes mainstream. But who should be explaining?

Bias in AI is an issue that has really come to the forefront in recent months — our recent blog post discussed the Apple Card/Goldman Sachs alleged bias issue. And this isn’t an isolated instance: Racial bias in healthcare algorithms and bias in AI for judicial decisions are just a few more examples of rampant … Continue reading “Explainable AI goes mainstream. But who should be explaining?”

The never-ending issues around AI and bias. Who’s to blame when AI goes wrong?

We’ve seen it before, we’re seeing it again now with the recent Apple and Goldman Sachs alleged credit card bias issue, and we’ll very likely continue seeing it well into 2020 and beyond. Bias in AI is there, it’s usually hidden, (until it comes out), and it needs a foundational fix. This past weekend we … Continue reading “The never-ending issues around AI and bias. Who’s to blame when AI goes wrong?”

Explainable AI Podcast: S&P Global & Fiddler discuss AI, explainability, and machine learning

We recently chatted with Ganesh Nagarathnam, Director of Analytics and Machine Learning Engineering, at S&P Global. Take a listen to the podcast below or read the transcript. (Transcript edited for clarity and length.) Listen to all the Explainable AI Podcasts here Fiddler: Welcome to Fiddler’s explainable AI podcast. I’m Anusha Sethuraman. And today I have … Continue reading “Explainable AI Podcast: S&P Global & Fiddler discuss AI, explainability, and machine learning”